The following definitions are used herein in the specification and the appended claims. “Location determination” means determining a location of a certain device. Usually, location determination is assisted by installing a network of beacon-broadcasting stations at known locations over a region of interest such that when the device listens to the beacons sent out by these stations, the location of the device is estimable by the signal strengths of the received beacons or by the arrival times thereof. “Proximity determination” means determining a degree of proximity between a device and a certain beacon-broadcasting station. “A degree of proximity” is a descriptive qualifier for indicating how close a device is distant from a beacon-broadcasting station. As one example, a set of such descriptive qualifiers includes “immediate,” “near,” “far” and “unknown.” Note that proximity determination does not provide a quantitative value of distance between the device and the station. Proximity determination may be implemented by first measuring a received signal strength indicator (RSSI) value of the beacon sent out from the station. Then the measured RSSI value is mapped to a corresponding descriptive qualifier. This approach is usually employed for a Bluetooth Low Energy-(BLE-)enabled device. “A mobile computing device” is a portable electronic device having computing power, and configured to provide wireless communications and to support location or proximity determination. For example, a mobile computing device may be a BLE-enabled smartphone, or a handheld tablet computer equipped with BLE-compliant functionalities.
BLE signals from battery-driven beacon-broadcasting stations are at the core of the indoor location technology. A mobile computing device detects a beacon from one beacon-broadcasting station and can calculate roughly the distance to this station and hence estimate the location of the mobile computing device. The stations are placed at known locations around an area of interest and each station repeatedly transmits a radio beacon. When the mobile computing device detects the beacons transmitted by the stations, the position of the mobile computing device relative the stations can be determined by measuring RSSI values of the transmitted beacons. However, one practical problem encountered in BLE location-determining system is that BLE beacons are transmitted in an industrial, scientific and medical (ISM) band. The presence of co-channel interference, such as WiFi signals, introduces fluctuation of the measured RSSI values and hence reduces the location-determining accuracy achieved by the system. Another factor that increases RSSI fluctuation is the occurrence of multipath fading, especially in an indoor environment where location determination is required. It is desirable to reduce RSSI fluctuation in order to enhance location-determining accuracy in the presence of co-channel interference and multipath fading.
The BLE system is also useful for proximity determination. FIG. 1 depicts a practical scheme of partitioning a broadcasting coverage area 170 of a BLE beacon-generation station 105 into a plurality of zones for proximity determination. A first zone 110 of “immediate” is assigned for a region within 0.5 m from the station 105, a second zone 120 of “near” for another region between 0.5 m and 2 m, a third zone 130 of “far” for a farther region between 2 m to 30 m, and possibly an extra zone 140 of “unknown” classified as a region when a mobile computing device 107 is outside the broadcasting coverage area 170. Other partitioning schemes are also possible. In some schemes, the third zone 130 may be extended up to 50 m or even 100 m, depending on the transmitted power. However, in some location-based applications, the size of the third zone 130 may be considered too large. A scheme having finer zones is desirable. If the RSSI fluctuation due to co-channel interference and multipath fading can be reduced, the realization of such scheme is made easier.
Apart from the need to reduce RSSI fluctuation, there is another challenge encountered in BLE systems. For advanced solutions to location determination, where it is desired to locate a user of the mobile computing device accurately in a two-dimensional region and show the user's whereabouts (zone or position) on a map, several BLE beacon-broadcasting stations are required. Ideally, the stations have contiguous broadcasting coverage areas, usually the same in size, so that when the mobile computing navigates from one broadcasting coverage area to another, the station closest to the mobile computing device can be clearly identified. Practically, however, the broadcasting coverage areas of adjacent stations are usually overlapped. There is a chance that the mobile computing device falls into a jittering area between two or more zones. The jittering area is an area of overlap between zones. The presence of jittering area creates uncertainty in location determination in that the mobile computing device is unable to determine which one of two or more adjacent stations is closer to. It is also desirable if the jittering area can be reduced as much as possible.
Existing techniques attempting to increase positioning accuracy in location or proximity determination includes, for example, the following. In a system disclosed by CN103983266, movement directions and steps of a user are further monitored in addition to using beacons. In another system suggested by CN105353351, arrival times of multiple beacons are analyzed to improve the positioning accuracy. In yet another system disclosed by U.S. Pat. No. 8,965,411, different transmit powers for different beacons are employed, offering additional information useful for increasing the positioning accuracy. However, the aforementioned three systems have a common disadvantage that system design is significantly complicated. Applying the techniques used in these three systems to a BLE system implies considerable modification to the BLE system is required. In a system of US2015105099, each beacon is associated with a group value. Grouping may be based on multiple criteria including geographical location, work team assignment, transceiver type or other constraining information. Beacons with minority group values are then excluded in RSSI determination. However, RSSI fluctuation may introduce incorrect beacon exclusions and thus reduces the positioning accuracy. Furthermore, grouping results are required to be adjusted when new beacons are deployed. The latter disadvantage complicates the system design.
In view of the above-mentioned observations, there is a need in the art to have a technique for reducing RSSI fluctuation at a mobile computing device in the presence of co-channel interference and multipath fading during beacon signal measurement as well as for reducing the jittering area. The technique is not only for BLE systems but also useful to other wireless systems using beacons for the mobile computing device to perform location or proximity determination.